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senior-security高级保安

Agent Skill

用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。它适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时,应先确认最小权限、脱敏方式和操作边界。

总安装

15,961

周安装

652

GitHub Stars

26,362

下载量

5,112
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:senior-security(高级保安)
来源仓库:https://github.com/davila7/claude-code-templates
仓库路径:skills/senior-security
安装命令:
npx skills add https://github.com/davila7/claude-code-templates --skill senior-security
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/davila7/claude-code-templates --skill senior-security

简介

用于威胁建模、渗透测试、安全审计和加密实施的综合安全工具包。

  • 三个核心自动化脚本:用于搭建和最佳实践的 Threat Modeler、用于深入分析和建议的 Security Auditor 以及用于专家级测试自动化的 Pentest Automator
  • 包括涵盖安全架构模式、渗透测试工作流程以及带有代码示例和反模式的加密实现的参考文档
  • 支持跨 TypeScript、Python、Go 和移动平台的多个技术堆栈,并集成 Docker、Kubernetes、AWS、GCP 和 Azure
  • 内置质量检查、性能指标和自动修复,以及用于安全评估和合规性审核的可配置模板

SKILL.md

Senior Security

Complete toolkit for senior security with modern tools and best practices.

Quick Start

Main Capabilities

This skill provides three core capabilities through automated scripts:

# Script 1: Threat Modeler
python scripts/threat_modeler.py [options]

# Script 2: Security Auditor
python scripts/security_auditor.py [options]

# Script 3: Pentest Automator
python scripts/pentest_automator.py [options]

Core Capabilities

1. Threat Modeler

Automated tool for threat modeler tasks.

Features:

  • Automated scaffolding
  • Best practices built-in
  • Configurable templates
  • Quality checks

Usage:

python scripts/threat_modeler.py <project-path> [options]

2. Security Auditor

Comprehensive analysis and optimization tool.

Features:

  • Deep analysis
  • Performance metrics
  • Recommendations
  • Automated fixes

Usage:

python scripts/security_auditor.py <target-path> [--verbose]

3. Pentest Automator

Advanced tooling for specialized tasks.

Features:

  • Expert-level automation
  • Custom configurations
  • Integration ready
  • Production-grade output

Usage:

python scripts/pentest_automator.py [arguments] [options]

Reference Documentation

Security Architecture Patterns

Comprehensive guide available in references/security_architecture_patterns.md:

  • Detailed patterns and practices
  • Code examples
  • Best practices
  • Anti-patterns to avoid
  • Real-world scenarios

Penetration Testing Guide

Complete workflow documentation in references/penetration_testing_guide.md:

  • Step-by-step processes
  • Optimization strategies
  • Tool integrations
  • Performance tuning
  • Troubleshooting guide

Cryptography Implementation

Technical reference guide in references/cryptography_implementation.md:

  • Technology stack details
  • Configuration examples
  • Integration patterns
  • Security considerations
  • Scalability guidelines

Tech Stack

Languages: TypeScript, JavaScript, Python, Go, Swift, Kotlin Frontend: React, Next.js, React Native, Flutter Backend: Node.js, Express, GraphQL, REST APIs Database: PostgreSQL, Prisma, NeonDB, Supabase DevOps: Docker, Kubernetes, Terraform, GitHub Actions, CircleCI Cloud: AWS, GCP, Azure

Development Workflow

1. Setup and Configuration

# Install dependencies
npm install
# or
pip install -r requirements.txt

# Configure environment
cp .env.example .env

2. Run Quality Checks

# Use the analyzer script
python scripts/security_auditor.py .

# Review recommendations
# Apply fixes

3. Implement Best Practices

Follow the patterns and practices documented in:

  • references/security_architecture_patterns.md
  • references/penetration_testing_guide.md
  • references/cryptography_implementation.md

Best Practices Summary

Code Quality

  • Follow established patterns
  • Write comprehensive tests
  • Document decisions
  • Review regularly

Performance

  • Measure before optimizing
  • Use appropriate caching
  • Optimize critical paths
  • Monitor in production

Security

  • Validate all inputs
  • Use parameterized queries
  • Implement proper authentication
  • Keep dependencies updated

Maintainability

  • Write clear code
  • Use consistent naming
  • Add helpful comments
  • Keep it simple

Common Commands

# Development
npm run dev
npm run build
npm run test
npm run lint

# Analysis
python scripts/security_auditor.py .
python scripts/pentest_automator.py --analyze

# Deployment
docker build -t app:latest .
docker-compose up -d
kubectl apply -f k8s/

Troubleshooting

Common Issues

Check the comprehensive troubleshooting section in references/cryptography_implementation.md.

Getting Help

  • Review reference documentation
  • Check script output messages
  • Consult tech stack documentation
  • Review error logs

Resources

  • Pattern Reference: references/security_architecture_patterns.md
  • Workflow Guide: references/penetration_testing_guide.md
  • Technical Guide: references/cryptography_implementation.md
  • Tool Scripts: scripts/ directory

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

29.13%
按下载量换算1,489

Antigravity

24.68%
按下载量换算1,262

Cursor

19.56%
按下载量换算1,000

Gemini CLI

12.3%
按下载量换算629

OpenCode

7.1%
按下载量换算363

Codex

3.29%
按下载量换算168

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。

来源信息

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